Networked aggregation of localized particulate air pollutant sensors

ABSTRACT

Novel techniques are described for networked aggregation of distributed localized particulate air pollutant (LPAP) sensors. For example, a large number of sensors is distributed over a geographic region. Each sensor can detect local levels of one or more LPAPs, and can communicate the detected levels over one or more communications networks. A system can receive data samples for the LPAP levels from the sensors and can compute LPAP scores that are mapped to respective sub-regions of the geographic region. The computation can be a function of aggregating respective LPAP levels for at least those LPAP sensors in a particular sub-region of the geographic region, and also as a function of comparing the aggregation against an identified set of trigger thresholds for the LPAP of interest. In some cases, the computed and mapped LPAP scores can be output for display, for example, as a heat map, or the like.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/837,289, filed Apr. 1, 2020, which is a continuation of U.S. patentapplication Ser. No. 15/955,336, filed Apr. 17, 2018, the fulldisclosure of which are incorporated herein by reference.

FIELD

This invention relates generally to sensor device systems, and, moreparticularly, to networked aggregation of distributed localizedparticulate air pollutant sensors.

BACKGROUND

Some types of environmental pollution result from particulates trappedin the air, such as from cigarette and marijuana smoke. Theseparticulates can generally spread from their sources into surroundingareas, causing undesirable conditions, such as bad odors and harmfulsecond-hand smoke. A large subset of the population is concerned aboutthese types of generally localized environmental pollution. As anexample, builders, buyers, and users of schools, hospitals, homes, andthe like may not want to be in areas with high levels of suchpollutants. However, those affected portions of the population may nothave any practical and efficient way to obtain localized data regardingsuch pollutants.

BRIEF SUMMARY

Among other things, embodiments provide novel systems and methods fornetworked aggregation of distributed localized particulate air pollutantsensors. Embodiments operate in context of a large number of sensorsdistributed over a geographic region. Each sensor can detect levels in arespective location of one or more types of localized particulate airpollutant (LPAP), and can communicate the detected levels over one ormore communications networks.

A system can receive data samples for the LPAP levels from thenetwork-connected LPAP sensors and can compute LPAP scores that aremapped to respective sub-regions of the geographic region. Thecomputation can be a function of an aggregation of the respective LPAPlevels for at least those of the LPAP sensors having respective LPAPsensor locations corresponding to a respective sub-region of thegeographic region, and also as a function of comparing the aggregationagainst an identified set of trigger thresholds for the LPAP ofinterest. In some cases, the computed and mapped LPAP scores can beoutput for display, for example, as a heat map, or the like.

This summary is not intended to identify key or essential features ofthe claimed subject matter, nor is it intended to be used in isolationto determine the scope of the claimed subject matter. The subject mattershould be understood by reference to appropriate portions of the entirespecification of this patent, any or all drawings, and each claim.

The foregoing, together with other features and embodiments, will becomemore apparent upon referring to the following specification, claims, andaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is described in conjunction with the appendedfigures:

FIG. 1 shows an illustrative communications system for networkedaggregation of distributed localized particulate air pollutant (LPAP)sensors, according to various embodiments;

FIG. 2 shows an illustrative LPAP mapping environment, according tovarious embodiments;

FIG. 3 shows an example of a heat map generated according to variousembodiments;

FIG. 4 provides a schematic illustration of one embodiment of a computersystem that can implement various system components and/or performvarious steps of methods provided by various embodiments describedherein; and

FIG. 5 shows a flow diagram of an illustrative method, according tovarious embodiments.

In the appended figures, similar components and/or features may have thesame reference label. Further, various components of the same type maybe distinguished by following the reference label by a second label(e.g., a lower-case letter) that distinguishes among the similarcomponents. If only the first reference label is used in thespecification, the description is applicable to any one of the similarcomponents having the same first reference label irrespective of thesecond reference label.

DETAILED DESCRIPTION

Embodiments of the disclosed technology will become clearer whenreviewed in connection with the description of the figures herein below.In the following description, numerous specific details are set forth toprovide a thorough understanding of the present invention. However, onehaving ordinary skill in the art should recognize that the invention maybe practiced without these specific details. In some instances,circuits, structures, and techniques have not been shown in detail toavoid obscuring the present invention.

FIG. 1 shows an illustrative communications system 100 for networkedaggregation of distributed localized particulate air pollutant (LPAP)sensors, according to various embodiments. As used herein, the term“localized particulate air pollutant,” or “LPAP,” generally refers toany type of localized air pollution resulting from particulates in theair that can be disturbing or unhealthy for people or animals inproximity to the particulates. Typically, the LPAPs are associated withundesirable or harmful odors, smoke, fumes, or the like, such as fromcigarette smoke, marijuana smoke, certain manufacturing (e.g., fumesfrom a small leather tanning shop), certain artistic endeavors (e.g.,paint or other fumes), cooking (e.g., strong odors from certain types offood), etc. These particulates typically originate from a small source(e.g., a cigarette, restaurant kitchen, small printing press, etc.), andcan spread from the source into local surroundings. Certain populationscan benefit from an awareness of the presence and/or levels of certainLPAPs in certain locales. For example, builders, buyers, and users ofschools, hospitals, homes, and the like may not want to be in areas withhigh levels of certain LPAPs.

Embodiments described herein seek to process LPAP level data from acrosswide geographical areas and large numbers of sensors to provideaggregated LPAP level data. Such data can be used to compute LPAP scoresaccording to particular thresholds and to map the scores to differentresolutions of sub-regions. For example, in response to mappingrequests, embodiments can compute and generate heat maps, or the like,to indicate levels of selected LPAPs across selected sub-regions of ageographical region.

In general, the communications system 100 includes a large number ofnetwork-connected LPAP sensors 130 in communication, via one or morenetworks, with a LPAP mapping system 160. Each LPAP sensor 130 can beadapted to detect levels, in proximity to the LPAP sensor 130, of one ormore LPAPs. Each LPAP sensor 130 can be constructed and deployed in anysuitable manner. Some LPAP sensors 130 are implemented as stand-alonesensor systems having a sensor system on a chip housed in a housing withan integrated antenna (e.g., as an Internet of Things (IoT) device). Thesensor system on a chip can be designed to detect certain types ofparticulates in the air and can be coupled with a communications chipthat can communicate sensed levels via the antenna to one or morenetworks. Other LPAP sensors 130 can be integrated into another system,such as a weather station, residential satellite receiver, etc. SomeLPAP sensors 130 can be privately owned (e.g., owned by an individualhomeowner and installed in or on the customer's premises); while otherscan be owned by a communications services provider (e.g., a networkprovider), by a municipality, and or by any other suitable individual orentity.

The LPAP sensors 130 are typically deployed outside to detect outsideair particulate levels. However, some implementations support indoorLPAP sensors 130, as well. In such implementations, various techniquescan be used to discriminate data from indoor and outdoor LPAP sensors130 to avoid misleading sensor level information. As an example, supposea first cigarette smoke LPAP sensor 130 is disposed in the interior of arestaurant that permits smoking, and a second cigarette smoke LPAPsensor 130 is disposed on the exterior of the restaurant. For apotential buyer of a house across the street from the bar, it may bemisleading to characterize local LPAP levels based on the data from thefirst sensor; but a potential family deciding whether to eat at therestaurant may be much more interested in the LPAP level data from thefirst sensor. In these and other cases where it is useful todiscriminate between level data from different LPAP sensors 130 (ordifferent categories or types of LPAP sensors 130), received data can betreated differently (e.g., computed against different threshold levels,normalized differently, etc.), displayed differently (e.g., using colorcoding, or other indications), etc.

The LPAP sensors 130 can be in communication with the LPAP mappingsystem 160 over any suitable type of network or networks. Someembodiments of the LPAP sensors 130 are implemented as IoT devices andare in communication with an IoT network, such as a low-power narrowbandnetwork. In some embodiments, some or all LPAP sensors 130 includeantennas for communicating with a satellite or cellular network. Atypical satellite network can include one or more satellites 105 (e.g.,one or more low Earth orbit (LEO), medium Earth orbit (MEO),geostationary (GEO), or other satellites) in communication with groundnetwork components 107, such as gateways, satellite receivers, etc.using one or more satellite communication protocols. One or more of theground network components 107 is typically in communication with one ormore routing components 120, such as routers, switches, etc. Similarly,a typical cellular network can include multiple cellular base stations110 in communication with such routing components 120. Other types ofcommunications networks, such as cable or public switched telephonenetworks (PSTNs) can similarly be in communication with such routingcomponents 120. The routing components 120 can effectively provide thevarious networks with connectivity to the Internet and/or othernetworks, such as via a backhaul network 150, which can includefiber-optic or other suitable links.

The LPAP sensors 130 can be in communication with any of these or othersuitable types of networks. In some implementations, the LPAP sensors130 are in direct communication with the satellite(s) 105, cellular basestations 110, etc. via one or more integrated or coupled cellularantennas using one or more suitable communication protocols (e.g.,Long-Term Evolution (LTE) protocols, or the like). In suchimplementations, LPAP sensors 130 can gather LPAP level data andcommunicate the data directly to the satellite(s), cellular basestations, etc., which can forward the data to the LPAP mapping system160 via one or more intermediary networks. In other implementations, theLPAP sensors 130 are in indirect communication with the satellite(s)105, cellular base stations 110, etc. via one or more intermediarynetworks. FIG. 1 shows an illustrative intermediary network as a localarea network (LAN) 145 implemented by a local router 140. In such animplementation, the LPAP sensors 130 can include integrated or coupledantennas to communicate directly or indirectly with the local router 140using any suitable wired or wireless communication protocols (e.g.,WiFi, ZigBee, Bluetooth, Ethernet, etc.). In such implementations, LPAPsensors 130 can gather LPAP level data and communicate the data to thelocal router 140, which can then forward the data to one or morenetworks (e.g., a satellite, cellular, cable, PSTN, or other network)and/or one or more routing components 120 ultimately coupled with thebackhaul network 150.

The described network architectures are intended only to illustrate andinclude some of the possible implementations. For example, some of theabove-described networks can be implemented as hub-spoke configurations,peer-to-peer configurations, mesh configurations, or otherconfigurations. Further, the particular connections can be altered inany suitable manner. While the LPAP mapping system 160 is illustratedand described above as coupled via the backhaul network 150; the LPAPmapping system 160 can alternatively be disposed (partially orcompletely) within one or more of the other networks. For example, in asatellite network implementation, the LPAP mapping system 160 can beimplemented within a satellite gateway, or in another provider-sidecomponent.

FIG. 2 shows an illustrative LPAP mapping environment 200, according tovarious embodiments. The LPAP mapping environment 200 can be part of thecommunications system 100 of FIG. 1 , and can include an illustrativeLPAP mapping system 160 (illustrated as LPAP mapping system 160′). Forthe sake of context, the LPAP mapping system 160′ is illustrated as incommunication with a large number of LPAP sensors 130 via one or morenetworks 260. The one or more networks 260 can include any or all of thevarious types of networks illustrated and discussed with reference toFIG. 1 and/or any other suitable networks.

Embodiments of the LPAP mapping system 160′ include a trigger data store210, a mapping data store 220, an aggregation processor 230, and amapping processor 240. The trigger data store 210 and the mapping datastore 220 can be implemented using local storage devices (e.g., harddisk drives, solid state drives, registers, etc.), remote storage (e.g.,servers, cloud storage systems, etc.), and/or any other suitable type ofdata storage. For example, one or more non-transient processor-readablestorage devices can be used to implement both the trigger data store 210and the mapping data store 220. The trigger data store 210 can have,stored thereon, one or more trigger thresholds associated with one ormore LPAPs. In one implementation, studies have determined a safe level(e.g., as a safe concentration in the air, measured in parts pernotation, or the like) of a particular LPAP, and the safe level isstored as a single trigger threshold for the single corresponding LPAPin the trigger data store 210. In another implementation, a single suchtrigger threshold is stored for each of multiple types of LPAPs. Inanother implementation, multiple trigger thresholds are stored in thetrigger data store 210 for each of one or more LPAPs. For example, afirst trigger threshold can indicate a scientifically determined safelevel for adults, a second trigger threshold can indicate ascientifically determined safe level for children and pets, a thirdtrigger threshold can indicate an anecdotally generated level determinedto be bothersome to an average person, etc.

Some embodiments permit customers and/or other users to provide data foruse in determining trigger thresholds. In one embodiment, an application(e.g., for use on a smart phone or other mobile device) provides afeedback portal through which users can submit a current localizedreport on their subjective experience. As an example, a user walkingdown a street may experience a subjectively high exposure to marijuanasmoke and may rate the present level in the present location through theapplication. The rating can be sent back to the LPAP mapping system160′, which can use the rating in various ways. According to some uses,the subjective rating (or a collection of subjective ratingscrowd-sourced by multiple users) is compared to one or more objectiveLPAP level measurements from nearby LPAP sensors 130. The comparison canbe used to tune or set a trigger threshold, to generate statisticsregarding differences between subjective and objective measurements(e.g., to enable statistical generation of an objective “actual level”score and a subjective “feels like” score), to detect issues with LPAPsensors 130 (e.g., miscalibrated or broken sensors), etc. Other uses cantreat the data separately, for example, to provide separate objectiveand subjective data for various locales.

Embodiments of the aggregation processor 230 include a network interface235 coupled with the one or more communications networks 260 to receiveLPAP data samples from the network-connected LPAP sensors 130. Asdescribed above, the LPAP sensors 130 are distributed over thegeographic region, and each LPAP data sample indicates a respective LPAPlevel at a respective LPAP sensor location in the geographic region. Thesensor locations can correspond to various geographical definitions.Embodiments of the mapping data store 220 can have, stored thereon,geographical definitions for geographic sub-regions within a geographicregion. LPAP sensors 130 can be spread over a large geographical region,such as a city (e.g., or any larger or smaller region, such as aneighborhood, county, state, country, etc.). The mapping data store 220can include any suitable definitions for any suitable resolution ofsub-regions. The sub-regions can be as small as a single LPAP sensor 130location and as large as the geographic region of which it is asub-region. The geographical definitions can be stored in the mappingdata store 220 in any suitable manner. For example, the geographicdefinition can be a set of global positioning satellite (GPS)coordinates, latitude and longitude pairs, street addresses, mapcoordinate references, etc.

Embodiments of the mapping processor 240 are coupled with the triggerdata store 210, the mapping data store 220, and the aggregationprocessor 230. The mapping processor 240 can include a scoring interface245 to output LPAP scores. Each LPAP score is mapped to a respectivesub-region of the geographic region. Each LPAP score can be computed asa function of an aggregation of the respective LPAP levels for at leastthose of the LPAP sensors 130 having respective LPAP sensor locationscorresponding to the respective sub-region. For example, an LPAP scorecan be computed according to the respective resolution of the sub-region(e.g., for a particular LPAP sensor 130, for a particular neighborhoodblock, for a particular neighborhood, etc.). Each LPAP score can becomputed further as a function of comparing the aggregation against theset of trigger thresholds. In some implementations, the comparisoninvolves using the trigger thresholds as normalization data forconverting raw LPAP level data from the LPAP sensors 130 into a scorethat is intuitive to a human user, or the like. For example, the scorecan be on a scale from 0 to 100, regardless of the type of measurementused for that LPAP (e.g., parts per million, etc.). In otherimplementations, the computed score is only in relation to the triggerthreshold. For example, the score can simply indicate whether the levelsfor the LPAP are above or below the one or more trigger thresholds.

While some embodiments assume that the LPAP sensors 130 communicate rawLPAP level data to the LPAP mapping system 160′, other embodiments canreceive pre-processed data from some or all of the LPAP sensors 130. Forexample, some of the LPAP sensors 130 can convert collected LPAP levelsinto a normalized data stream, into a score, etc.; and the converteddata can be sent to the LPAP mapping system 160′. In other embodiments,some or all LPAP sensors 130 can include internal trigger thresholdsettings, and they may communicate LPAP level data in relation to thoseinternal trigger thresholds. For example, an LPAP sensor 130 may beconfigured to save power and/or bandwidth by communicating LPAP leveldata only periodically, only when the LPAP data exceeds (or falls below)an internal trigger threshold, or at any other suitable time.

In some embodiments, the LPAP mapping system 160′ further includes adisplay processor 250. The display processor 250 can be coupled with thescoring interface 245 and can include a portal interface 255. The portalinterface 255 can be coupled with the network(s) 260 so as to beaccessible by display devices 265, such as a smart phone, computer,television, or any other computational system having a suitable displayand corresponding display and communication hardware and software forreceiving and displaying data described herein. Embodiments can receivea map display output generated by the display processor 250 as afunction of the LPAP scores. The map display output can be generatedand/or communicated in response to a mapping request received from thedisplay device. For example, a user can issue (e.g., via a graphicaluser interface) a mapping request for a particular set of LPAP levelscorresponding to one or more LPAPs across one or more sub-regions, andthe map display output can be generated and/or communicated,accordingly.

In some cases, LPAP scores and/or the map display output can begenerated in response to the mapping request. For example, the mappingrequest can indicate a selected one or more LPAPs and a selected one ormore sub-regions, and the LPAP scores and/or map display output can begenerated in response to the request for the selected parameters. Inother cases, the LPAP scores and/or the map display output can begenerated prior to receiving a mapping request. For example, variousLPAP scores and/or map display outputs can be pre-computed and/orpre-generated and stored in the mapping data store 220 for subsequentuse in fulfilling mapping requests. Some embodiments of the mapping datastore 220 thus can store historical data, such as historical raw LPAPlevel data from the LPAP sensors 130, historical subjective data fromusers or studies, historical computed LPAP scores, etc. In oneembodiment, such historical data is used to generate map display outputsin response to a mapping request designating a particular historicaltime or time range. In another embodiment, such historical data is usedto generate statistical and/or other computations, such as tointerpolate, extrapolate, and/or predict LPAP data for particularlocations and/or times. Such computations can be used, for example, tocompare actual present levels to predicted present levels, to generatepredicted map display outputs for future times, etc.

In some implementations, the map display output includes a heat mapindicating the respective LPAP scores mapped for a plurality of thesub-regions. FIG. 3 shows an example of a heat map 300 generatedaccording to various embodiments. The heat map can be generated by oneof the display devices 265 according to the map display output receivedfrom the display processor 250 and generated by the mapping processor240. The illustrated heat map 300 shows LPAP level data across multiplesub-regions 315 of a geographical region 310. As illustrated, differentlevels of a particular LPAP can be indicated by color, shading, or inany other suitable manner.

A computer system as illustrated in FIG. 4 may be incorporated as partof the previously described computerized devices. FIG. 4 provides aschematic illustration of one embodiment of a computer system 400 thatcan implement various system components and/or perform various steps ofmethods provided by various embodiments described herein. It should benoted that FIG. 4 is meant only to provide a generalized illustration ofvarious components, any or all of which may be utilized as appropriate.FIG. 4 , therefore, broadly illustrates how individual system elementsmay be implemented in a relatively separated or relatively moreintegrated manner.

The computer system 400 is shown comprising hardware elements that canbe electrically coupled via a bus 405 (or may otherwise be incommunication, as appropriate). The hardware elements may include one ormore processors 410, including, without limitation, one or moregeneral-purpose processors and/or one or more special-purpose processors(such as digital signal processing chips, graphics accelerationprocessors, video decoders, and/or the like); one or more input devices415, which can include, without limitation, a mouse, a keyboard, remotecontrol, and/or the like; and one or more output devices 420, which caninclude, without limitation, a display device, a printer, and/or thelike.

The computer system 400 may further include (and/or be in communicationwith) one or more non-transitory storage devices 425, which cancomprise, without limitation, local and/or network accessible storage,and/or can include, without limitation, a disk drive, a drive array, anoptical storage device, a solid-state storage device, such as a randomaccess memory (“RAM”), and/or a read-only memory (“ROM”), which can beprogrammable, flash-updateable and/or the like. Such storage devices maybe configured to implement any appropriate data stores, including,without limitation, various file systems, database structures, and/orthe like.

The computer system 400 might also include a communications subsystem430, which can include, without limitation, a modem, a network card(wireless or wired), an infrared communication device, a wirelesscommunication device, and/or a chipset (such as a Bluetooth™ device, an402.11 device, a WiFi device, a WiMax device, cellular communicationdevice, etc.), and/or the like. The communications subsystem 430 maypermit data to be exchanged with a network (such as the networkdescribed below, to name one example), other computer systems, and/orany other devices described herein. In many embodiments, the computersystem 400 will further comprise a working memory 435, which can includea RAM or ROM device, as described above.

The computer system 400 also can comprise software elements, shown ascurrently being located within the working memory 435, including anoperating system 440, device drivers, executable libraries, and/or othercode, such as one or more application programs 445, which may comprisecomputer programs provided by various embodiments, and/or may bedesigned to implement methods, and/or configure systems, provided byother embodiments, as described herein. Merely by way of example, one ormore procedures described with respect to the method(s) discussed abovemight be implemented as code and/or instructions executable by acomputer (and/or a processor within a computer); in an aspect, then,such code and/or instructions can be used to configure and/or adapt ageneral purpose computer (or other device) to perform one or moreoperations in accordance with the described methods.

A set of these instructions and/or codes might be stored on anon-transitory computer-readable storage medium, such as thenon-transitory storage device(s) 425 described above. In some cases, thestorage medium might be incorporated within a computer system, such ascomputer system 400. In other embodiments, the storage medium might beseparate from a computer system (e.g., a removable medium, such as acompact disc), and/or provided in an installation package, such that thestorage medium can be used to program, configure, and/or adapt a generalpurpose computer with the instructions/code stored thereon. Theseinstructions might take the form of executable code, which is executableby the computer system 400 and/or might take the form of source and/orinstallable code, which, upon compilation and/or installation on thecomputer system 400 (e.g., using any of a variety of generally availablecompilers, installation programs, compression/decompression utilities,etc.), then takes the form of executable code.

As an example, embodiments of the non-transitory computer-readablestorage medium include processor-readable instructions that cause one ormore processors 410 of a network-aggregated LPAP mapping system toperform various steps. The processor(s) 410 can receive data samples fora LPAP via a communications network (e.g., via the communicationssubsystem 430) from network-connected LPAP sensors distributed over ageographic region. Each LPAP data sample can indicate a respective LPAPlevel at a respective LPAP sensor location in the geographic region. Aset of trigger thresholds associated with the LPAP (e.g., stored in thestorage device(s) 425 and/or in working memory 435) can be identified.The processor(s) 410 can compute LPAP scores, each mapped to arespective sub-region of the geographic region. Each LPAP score can becomputed as a function of an aggregation of the respective LPAP levelsfor at least those of the LPAP sensors having respective LPAP sensorlocations corresponding to a respective sub-region of the geographicregion, and as a function of comparing the aggregation against anidentified set of trigger thresholds. In some embodiments, the set oftrigger thresholds associated with the LPAP, and/or geographicaldefinitions for the plurality of geographic sub-regions of thegeographic region, can be stored in the storage device(s) 425 and/or inworking memory 435. In some implementations, the processor(s) 410 canoutput the LPAP scores for display. For example, a mapping request canbe received (e.g., via the communications subsystem 430 and/or via oneor more input devices 415) that indicates a selected set of thesub-regions, and the processor(s) 410 can output the LPAP scores fordisplay by generating a map display output to indicate the respectiveLPAP scores for the requested selected set of the sub-regions.

It will be apparent to those skilled in the art that substantialvariations may be made in accordance with specific requirements. Forexample, customized hardware might also be used, and/or particularelements might be implemented in hardware, software (including portablesoftware, such as applets, etc.), or both. Further, connection to othercomputing devices, such as network input/output devices, may beemployed.

As mentioned above, in one aspect, some embodiments may employ acomputer system (such as the computer system 400) to perform methods inaccordance with various embodiments of the invention. According to a setof embodiments, some or all of the procedures of such methods areperformed by the computer system 400 in response to processor 410executing one or more sequences of one or more instructions (which mightbe incorporated into the operating system 440 and/or other code, such asan application program 445) contained in the working memory 435. Suchinstructions may be read into the working memory 435 from anothercomputer-readable medium, such as one or more of the non-transitorystorage device(s) 425. Merely by way of example, execution of thesequences of instructions contained in the working memory 435 mightcause the processor(s) 410 to perform one or more procedures of themethods described herein.

The terms “machine-readable medium,” “computer-readable storage medium”and “computer-readable medium,” as used herein, refer to any medium thatparticipates in providing data that causes a machine to operate in aspecific fashion. These mediums may be non-transitory. In an embodimentimplemented using the computer system 400, various computer-readablemedia might be involved in providing instructions/code to processor(s)410 for execution and/or might be used to store and/or carry suchinstructions/code. In many implementations, a computer-readable mediumis a physical and/or tangible storage medium. Such a medium may take theform of a non-volatile media or volatile media. Non-volatile mediainclude, for example, optical and/or magnetic disks, such as thenon-transitory storage device(s) 425. Volatile media include, withoutlimitation, dynamic memory, such as the working memory 435.

Common forms of physical and/or tangible computer-readable mediainclude, for example, a floppy disk, a flexible disk, hard disk,magnetic tape, or any other magnetic medium, a CD-ROM, any other opticalmedium, any other physical medium with patterns of marks, a RAM, a PROM,EPROM, a FLASH-EPROM, any other memory chip or cartridge, or any othermedium from which a computer can read instructions and/or code.

Various forms of computer-readable media may be involved in carrying oneor more sequences of one or more instructions to the processor(s) 410for execution. Merely by way of example, the instructions may initiallybe carried on a magnetic disk and/or optical disc of a remote computer.A remote computer might load the instructions into its dynamic memoryand send the instructions as signals over a transmission medium to bereceived and/or executed by the computer system 400.

The communications subsystem 430 (and/or components thereof) generallywill receive signals, and the bus 405 then might carry the signals(and/or the data, instructions, etc., carried by the signals) to theworking memory 435, from which the processor(s) 410 retrieves andexecutes the instructions. The instructions received by the workingmemory 435 may optionally be stored on a non-transitory storage device425 either before or after execution by the processor(s) 410.

It should further be understood that the components of computer system400 can be distributed across a network. For example, some processingmay be performed in one location using a first processor while otherprocessing may be performed by another processor remote from the firstprocessor. Other components of computer system 400 may be similarlydistributed. As such, computer system 400 may be interpreted as adistributed computing system that performs processing in multiplelocations. In some instances, computer system 400 may be interpreted asa single computing device, such as a distinct laptop, desktop computer,or the like, depending on the context.

Systems including those described above can be used to implement variousmethods 500. FIG. 5 shows a flow diagram of an illustrative method 500,according to various embodiments. Embodiments of the method 500 begin atstage 504 by receiving data samples for a LPAP via a communicationsnetwork from network-connected LPAP sensors distributed over ageographic region. Each LPAP data sample can indicate a respective LPAPlevel at a respective LPAP sensor location in the geographic region. Atstage 508, embodiments can identify a set of trigger thresholdsassociated with the LPAP. At stage 512, embodiments can compute LPAPscores, each mapped to a respective sub-region of the geographic region.Each LPAP score can be computed as a function of an aggregation of therespective LPAP levels for at least those of the LPAP sensors havingrespective LPAP sensor locations corresponding to a respectivesub-region of the geographic region, and as a function of comparing theaggregation against the set of trigger thresholds.

At stage 516, embodiments can output the LPAP scores for display. Insome embodiments, at stage 520, a mapping request can be received from adisplay device via the communications network, and the mapping requestcan indicate a selected set of the sub-regions. In such embodiments, theoutputting at stage 516 can include generating a map display output inresponse to the mapping request to indicate the respective LPAP scoresfor the selected one or more of the sub-regions. For example, generatingthe map display output can include generating a heat map indicating therespective LPAP scores for the selected set of the sub-regions mapped ingraphical relationship to a graphical representation of the selected setof the sub-regions. In some such embodiments, the set of triggerthresholds includes a first trigger threshold indicating a predefinedunsafe LPAP level and a second trigger threshold indicating a predefinedundesirable LPAP level that is lower than the first trigger threshold,and the heat map is generated to graphically distinguish between localeshaving LPAP levels higher than the first threshold, locales having LPAPlevels lower than the first threshold and higher than the secondthreshold, and locales having LPAP levels lower than the secondthreshold.

In other embodiments, the LPAP data samples indicate respective LPAPlevels at respective LPAP sensor locations in the geographic region foreach of multiple different LPAPs (e.g., cigarette smoke, marijuanasmoke, smoke from a small factory, etc. In such embodiments, computingthe LPAP scores at stage 512 can include computing respective LPAPscores for each of the different LPAPs. In some such cases, theidentifying at stage 508 can include identifying a respective set oftrigger thresholds associated with each of the LPAPs. In someembodiments, at stage 520, the mapping request received from the displaydevice can additionally or alternatively indicate a selected one or moreof the LPAPs; and the outputting at stage 516 cab include generating themap display output in response to the mapping request to indicate therespective LPAP scores for each of the selected set of LPAPs (e.g., ineach of the selected set of the sub-regions).

The methods, systems, and devices discussed above are examples. Variousconfigurations may omit, substitute, or add various procedures orcomponents as appropriate. For instance, in alternative configurations,the methods may be performed in an order different from that described,and/or various stages may be added, omitted, and/or combined. Also,features described with respect to certain configurations may becombined in various other configurations. Different aspects and elementsof the configurations may be combined in a similar manner. Also,technology evolves and, thus, many of the elements are examples and donot limit the scope of the disclosure or claims.

Specific details are given in the description to provide a thoroughunderstanding of example configurations (including implementations).However, configurations may be practiced without these specific details.For example, well-known circuits, processes, algorithms, structures, andtechniques have been shown without unnecessary detail in order to avoidobscuring the configurations. This description provides exampleconfigurations only, and does not limit the scope, applicability, orconfigurations of the claims. Rather, the preceding description of theconfigurations will provide those skilled in the art with an enablingdescription for implementing described techniques. Various changes maybe made in the function and arrangement of elements without departingfrom the spirit or scope of the disclosure.

Also, configurations may be described as a process which is depicted asa flow diagram or block diagram. Although each may describe theoperations as a sequential process, many of the operations can beperformed in parallel or concurrently. In addition, the order of theoperations may be rearranged. A process may have additional steps notincluded in the figure. Furthermore, examples of the methods may beimplemented by hardware, software, firmware, middleware, microcode,hardware description languages, or any combination thereof. Whenimplemented in software, firmware, middleware, or microcode, the programcode or code segments to perform the necessary tasks may be stored in anon-transitory computer-readable medium such as a storage medium.Processors may perform the described tasks.

Having described several example configurations, various modifications,alternative constructions, and equivalents may be used without departingfrom the spirit of the disclosure. For example, the above elements maybe components of a larger system, wherein other rules may takeprecedence over or otherwise modify the application of the invention.Also, a number of steps may be undertaken before, during, or after theabove elements are considered.

What is claimed is:
 1. A system comprising: a localized particulate airpollutant (LPAP) mapping system comprising a network interface tocommunicatively couple, via a network, with: a plurality of LPAP sensorsdistributed over a geographic region, each LPAP sensor to obtainrespective LPAP data samples from a respective LPAP sensor location, therespective LPAP data samples indicating measured levels of a particularLPAP, and a plurality of users, each via a feedback portal application,the LPAP mapping system to: receive, from one or more of the pluralityof users via the feedback portal application, one or more currentlocalized reports indicating one or more ratings of subjectiveLPAP-related experiences of the one or more users in a location;compute, for a predefined geographic sub-region of the geographic regioncorresponding to the location, an aggregated LPAP level based on therespective LPAP data samples obtained via the network from those of theLPAP sensors having respective LPAP sensor locations determined to bewithin the predefined geographic sub-region; and generating an outputfor the predefined geographic sub-region based on comparing the one ormore current localized reports for the location with the aggregated LPAPlevel for the corresponding predefined geographic sub-region.
 2. Thesystem of claim 1, wherein the comparing comprises statisticallygenerating a subjective score from the one or more current localizedreports for the location, statistically generating an objective scorefrom the aggregated LPAP level, and generating the output to indicate adifference between the subjective score and the objective score.
 3. Thesystem of claim 1, wherein the generating the output comprisesdetecting, based on the comparing, a miscalibrated or broken sensorissue with one or more of those of the LPAP sensors having respectiveLPAP sensor locations determined to be within the predefined geographicsub-region.
 4. The system of claim 1, wherein the generating the outputcomprises: generating or tuning a set of trigger thresholds based on theone or more current localized reports; and generating an LPAP score as afunction of comparing the aggregated LPAP level to the stored set oftrigger thresholds.
 5. The system of claim 1, wherein: at least one ofthe one or more current localized reports is historical data indicatingone or more ratings of subjective LPAP-related experiences of the one ormore users in a location at first one or more historical times prior toa present time; and the aggregated LPAP level is based at least in parton the respective LPAP data samples obtained at the present time via thenetwork from those of the LPAP sensors having respective LPAP sensorlocations determined to be within the predefined geographic sub-region.6. The system of claim 5, wherein: the aggregated LPAP level is basedfurther on respective LPAP data samples obtained at second one or morehistorical times via the network from those of the LPAP sensors havingrespective LPAP sensor locations determined to be within the predefinedgeographic sub-region.
 7. The system of claim 1, wherein the generatingthe output comprises: generating a map display output that graphicallyindicates at least a portion of the geographic region that includes thepredefined geographic sub-region, and graphically indicates an LPAPscore for the predefined geographic sub-region computed based on thecomparing the one or more current localized reports for the locationwith the aggregated LPAP level for the corresponding predefinedgeographic sub-region.
 8. A system comprising: a localized particulateair pollutant (LPAP) mapping system comprising a network interface tocommunicatively couple, via a network, with a plurality of LPAP sensorsdistributed over a geographic region, each LPAP sensor to obtainrespective LPAP data samples from a respective LPAP sensor location, therespective LPAP data samples indicating measured levels of a particularLPAP, wherein a first portion of the LPAP sensors are located inrespective outdoor locations, and a second portion of the LPAP sensorsare located in respective indoor locations; and a display processor toreceive a mapping request from a display device and to direct generationof an output on the display device in response to the mapping request,the mapping request indicating a location, wherein the LPAP mappingsystem is to generate the output responsive to the mapping request tocharacterize outdoor LPAP levels and/or the indoor LPAP levels for thelocation, such that: characterizing the outdoor LPAP levels in thelocation is based on computing, for a predefined geographic sub-regionof the geographic region corresponding to the location, an aggregatedLPAP level based on the respective LPAP data samples obtained via thenetwork from those of the first portion of the LPAP sensors havingrespective LPAP sensor locations determined to be within the predefinedgeographic sub-region; and characterizing the indoor LPAP levels in thelocation is based on one or more of the respective LPAP data samplesobtained via the network from one or more of the second portion of theLPAP sensors having respective LPAP sensor locations determined to bewithin the predefined geographic sub-region.
 9. The system of claim 8,wherein: the characterizing the outdoor LPAP levels is further based oncomparing the aggregated LPAP level to a first stored set of triggerthresholds; and the characterizing the indoor LPAP levels is furtherbased on comparing the one or more of the respective LPAP data samplesto a second stored set of trigger thresholds.
 10. The system of claim 8,wherein the LPAP mapping system is to generate the output responsive tothe mapping request by: generating a map display output that graphicallyindicates at least a portion of the geographic region that includes thepredefined geographic sub-region, and graphically characterizes theoutdoor LPAP levels and/or the indoor LPAP levels.
 11. The system ofclaim 8, wherein the LPAP mapping system is to generate the outputresponsive to the mapping request by: generating a map display outputthat graphically indicates at least a portion of the geographic regionthat includes the predefined geographic sub-region, and graphicallycharacterizes both the outdoor LPAP levels and the indoor LPAP levelsand graphically discriminating between the outdoor LPAP levels and theindoor LPAP levels.
 12. A method comprising: receiving, via a network, aplurality of localized particulate air pollutant (LPAP) samples from aplurality of LPAP sensors distributed over a geographic region, eachLPAP sensor to obtain respective LPAP data samples from a respectiveLPAP sensor location, the respective LPAP data samples indicatingmeasured levels of a particular LPAP, wherein a first portion of theLPAP sensors are located in respective outdoor locations, and a secondportion of the LPAP sensors are located in respective indoor locations;receiving a mapping request from a display device, the mapping requestindicating a location; and generating an output for display on thedisplay device in response to the mapping request to characterizeoutdoor LPAP levels and/or the indoor LPAP levels for the location, suchthat: characterizing the outdoor LPAP levels in the location is based oncomputing, for a predefined geographic sub-region of the geographicregion corresponding to the location, an aggregated LPAP level based onthe respective LPAP data samples obtained via the network from those ofthe first portion of the LPAP sensors having respective LPAP sensorlocations determined to be within the predefined geographic sub-region;and characterizing the indoor LPAP levels in the location is based onone or more of the respective LPAP data samples obtained via the networkfrom one or more of the second portion of the LPAP sensors havingrespective LPAP sensor locations determined to be within the predefinedgeographic sub-region.
 13. The method of claim 12, wherein: thecharacterizing the outdoor LPAP levels is further based on comparing theaggregated LPAP level to a first stored set of trigger thresholds; andthe characterizing the indoor LPAP levels is further based on comparingthe one or more of the respective LPAP data samples to a second storedset of trigger thresholds.
 14. The method of claim 12, wherein thegenerating the output responsive to the mapping request comprises:generating a map display output that graphically indicates at least aportion of the geographic region that includes the predefined geographicsub-region, and graphically characterizes the outdoor LPAP levels and/orthe indoor LPAP levels.
 15. The method of claim 12, wherein thegenerating the output responsive to the mapping request comprises:generating a map display output that graphically indicates at least aportion of the geographic region that includes the predefined geographicsub-region, and graphically characterizes both the outdoor LPAP levelsand the indoor LPAP levels and graphically discriminating between theoutdoor LPAP levels and the indoor LPAP levels.
 16. The method of claim12, further comprising: receiving, from a plurality of users, each via afeedback portal application, one or more current localized reportsindicating one or more ratings of subjective LPAP-related experiences ofthe one or more users in the location, wherein the generating the outputresponsive to the mapping request further comprises comparing the one ormore current localized reports for the location with the outdoor LPAPlevels and/or comparing the one or more current localized reports forthe location with the indoor LPAP levels.
 17. The method of claim 16,wherein the comparing comprises statistically generating a subjectivescore from the one or more current localized reports for the location,statistically generating an objective score from the outdoor LPAP levelsand/or the indoor LPAP levels, and generating the output to indicate adifference between the subjective score and the objective score.
 18. Themethod of claim 16, wherein the generating the output comprisesdetecting, based on the comparing, a miscalibrated or broken sensorissue with one or more of those of the LPAP sensors having respectiveLPAP sensor locations determined to be within the predefined geographicsub-region.
 19. The method of claim 16, wherein the generating theoutput comprises: generating or tuning a set of trigger thresholds basedon the one or more current localized reports; and generating an LPAPscore as a function of comparing the outdoor LPAP level and/or theindoor LPAP level to the stored set of trigger thresholds.
 20. Themethod of claim 19, wherein the generating the output responsive to themapping request comprises: generating a map display output thatgraphically indicates at least a portion of the geographic region thatincludes the predefined geographic sub-region, and graphically indicatesan LPAP score for the location computed based on the comparing.